(3.239.33.139) 您好!臺灣時間:2021/03/02 16:51
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:蘇宗平
研究生(外文):Tsung-Ping Su
論文名稱:漸進式零樹編碼系統之研究與架構設計
論文名稱(外文):Study and Architecture Design of a Progressive Zerotree Coding System
指導教授:謝明得謝明得引用關係
指導教授(外文):Ming-Der Shieh
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:電子與資訊工程研究所碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2001
畢業學年度:89
語文別:中文
論文頁數:65
中文關鍵詞:嵌入式零樹小波超大型積體電路影像壓縮低位元率
外文關鍵詞:EZWSPIHTVLSIlow bit rateimage compression
相關次數:
  • 被引用被引用:3
  • 點閱點閱:201
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:12
  • 收藏至我的研究室書目清單書目收藏:0
在現今網路盛行的時代,使用者對於影音多媒體效果的要求,使得在網路上傳送影音資料變得非常頻繁,其中又以影像資料最佔頻寬,這也使得使用者因網路頻寬的不足,而增加了等待的時間,通常為了降低影像資料的傳輸量,在數位影像的傳輸與儲存的應用上,低位元率(low bit rate)壓縮方法是必要的。目前已有多個影像編碼技術被提出,其中又以小波轉換(wavelet transform)提供了最佳的影像編碼應用。在小波轉換的基礎下,EZW (Embedded Zerotree Wavelet)與SPIHT(Set Partitioning In Hierarchical Trees)這兩種演算法,被廣泛應用在影像壓縮上,且嵌入式小波影像壓縮編碼都具備漸進式傳輸,精確性控制編碼長度及容錯等優點。另外,嵌入式影像處理可應用於即時(real-time)壓縮系統,但若要做為即時的壓縮高解析的靜態或動態影像,則必須使用數位信號處理器(DSP)或超大型積體電路(VLSI)來實現它。所以本論文將深入探討這兩種演算法之特性,著重於影像之EZW編碼演算法硬體架構推導與設計,並將EZW演算法加以改良,使之適用於實際超大型積體電路硬體實現。最後經由相關的電腦輔助設計軟體的協助下完成電路設計及功能模擬驗證。

In the network era, video/audio transmission is frequent due to the demand of multimedia users. Because video/image data takes most of bandwidth, which is usually deficient in such an application, users have to wait for a longer period to access the image data through network. To lower the amount of transmitted image data, low-bit-rate compression is then necessary in image transmission and storage. There are several techniques of image coding being mentioned so far, and among them, the wavelet transform offers the best way in image coding. On the basis of wavelet transform, the EZW (Embedded Zerotree Wavelet) and SPIHT (Set Partitioning In Hierarchical Trees) are widely used in the image compression. The embedded compression technique provides several superior properties like progressive transmission, coding-length-control, and fault tolerance such that it can be applied for real-time compression systems. In conjunction with the DSP (digital signal processor) or ASIC (application specific integrated circuit) realization, real-time compression can be further achieved for high-resolution moving or still images. This thesis is to explore the characteristics of both EZW and SPIHT and focuses on the design of EZW. In the meanwhile, we modify the existing EZW so as to fit in the VLSI implementation. Finally, this thesis concludes with the demonstration of the resulting functional verification and performance evaluation.

中文摘要---------------------------------------------i
英文摘要---------------------------------------------ii
致謝---------------------------------------------iii
目錄---------------------------------------------iv
圖目錄---------------------------------------------vi
表目錄---------------------------------------------viii
一、序論----------------------------------------------1
1.1 研究動機--------------------------------------1
1.2 研究目標--------------------------------------2
1.3 論文摘要--------------------------------------2
二、漸進式編碼演算法----------------------------------3
2.1 簡介------------------------------------------3
2.2 EZW演算法-------------------------------------4
2.3 EZW演算法範例---------------------------------10
2.4 EZW演算法模擬---------------------------------13
2.5 SPIHT演算法-----------------------------------15
2.6 SPIHT演算法範例-------------------------------20
2.7 SPIHT演算法模擬-------------------------------23
三、漸進式編碼硬體架構之相關研究----------------------24
3.1 簡介------------------------------------------24
3.2 EZW硬體架構相關研究---------------------------24
3.3 SPIHT硬體架構相關研究-------------------------34
四、嵌入式零樹編碼硬體架構設計------------------------37
4.1 簡介------------------------------------------37
4.2 深度搜尋與廣度搜尋----------------------------38
4.3 硬體版本之EZW演算法模擬-----------------------41
4.4 EZW編碼器架構設計-----------------------------42
4.5 記憶體空間需求--------------------------------49
五、硬體實現與結果模擬--------------------------------50
5.1 簡介------------------------------------------50
5.2 設計流程--------------------------------------50
5.3 EZW編碼器硬體模擬環境與模擬結果---------------53
5.4 硬體架構閘數統計------------------------------54
5.5 EZW編碼系統硬體架構比較-----------------------55
5.6 EZW編碼實例-----------------------------------56
六、結論與未來發展------------------------------------59
參考文獻----------------------------------------------60
自傳--------------------------------------------------65

[1]K. Sayood, Introduction to Data Compression, 2th, Academic Press, San Diego, 2000.
[2]V. Bhaskaran and K. Konstantinides, Image and Video Compression Standards Algorithms and Architectures, Kluwer Academic Publishers, Massachusetts, 1995.
[3]S. Katzenbeisser and F. Petitcolas, Information Hiding Techniques for Steganography and Digital Watermarking, Artech House, Norwood, 2000.
[4]S. F. Hsiao, Y. C. Tai and K. H. Chang, “VLSI Design of an Efficient Embedded Zerotree Wavelet Coder with Function of Digital Watermarking,” IEEE Transactions on Consumer Electronics, Vol. 463, Aug. 2000, Page(s): 628-636.
[5]S. Patel and S. Srinivasan, ”Modified Embedded Zerotree Wavelet Algorithm for Fast Implementation of Wavelet Image Codec,” Electronics Letters Vol. 3620, 28 Sept. 2000, Page(s): 1713-1714.
[6]K. Wiatr and P. Russek, ”Embedded Zero Wavelet Coefficient Coding Method for FPGA Implementation of Video Codec in Real-Time Systems,” Proceedings of the International Conference on Information Technology: Coding and Computing, 2000, Page(s): 146-151.
[7]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”VLSI Architecture for Very High Resolution Scalable Video Coding Using the Virtual Zerotree,” IEEE Workshop on Signal Processing Systems, 1999, Page(s): 131-140.
[8]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”EZW Algorithm Using Depth-First Representation of the Wavelet Zerotree,” Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, Vol. 1, 1999, Page(s): 75-78.
[9]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”Parallel Architecture for the Implementation of the Embedded Zerotree Wavelet Algorithm, ” 5th Australasian Conference in Computer Architecture, 1999, Page(s): 3-8.
[10]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”VLSI Architecture for Embedded Zerotree Wavelet Coding,” International Symposium on DSP for Communication Systems, Feb. 1999, Page(s): 128-133.
[11]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”VLSI Decoder Architecture for Embedded Zerotree Wavelet Algorithm,” IEEE Trans. Circuits and Systems, 1999, Page(s): 141-144.
[12]R. Y. Omaki, G. Fujita, T. Onaye, and I. Shirakawa, ”Architecture of Embedded Zerotree Wavelet Based Real-Time Video Coder,” Proceedings IEEE International Conference on ASIC/SOC, Page(s): 137-141.
[13]W. K. Lin, B.W. Ng, and N. Burgess, ”Reduced Memory Zerotree Coding for Hardware Implementation,” IEEE Trans. Multimedia Computing and Systems. Vol.2, 1999, Page(s):57-61.
[14]H. N. Cheung, G. Alagoda, K. Eshraghian, and L. M. Ang, ”Smart Pixel VLSI Architecture for Embedded Zerotree Wavelet Coding,” Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, Vol. 2, 1999, Page(s): 693-696.
[15]L. M. Ang, H. N. Cheung and K. Eshraghian, ”Robust Image Compression Using the Depth-First Search on the Wavelet Zerotree,” Proceedings of the Fifth International Symposium on Signal Processing and Its Applications, Vol. 2, 1999, Page(s): 797-800.
[16]W. K. Lin and N. Burgess, ”Low Memory Color Image Zerotree Coding,” Proceedings Information, Decision and Control, 1999, Page(s): 91-95.
[17]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”VLSI Architecture for Significance Map Coding of Embedded Zerotree Wavelet Coefficient,” IEEE Trans. Circuits and Systems, 1998, Page(s): 627-630.
[18]C. D. Creusere, ”Successive Coefficient Refinement for Embedded Lossless Image Compression,” Proceedings, 1998 International Conference on Image Processing, Vol. 1, 1998, Page(s): 521-525.
[19]J. Bae and V. K. Prasanna, ”A Fast and Area-Efficient VLSI Architecture for Embedded Image Coding,” Proceedings, International Conference on Image Processing, Vol. 3, 1995, Page(s): 452 -455.
[20]J. M. Shapiro, ”Embedded Image Coding Using Zerotrees of Wavelet Coefficients,” IEEE Transactions on Signal Processing, Vol. 4112, Dec. 1993, Page(s): 3445-3462.
[21]J. M. Shapiro, ”An Embedded Wavelet Hierarchical Image Coder,” IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 4, 1992, Page(s): 657-660.
[22]L. M. Ang and H. N. Cheung, ”Hardware Implementation of the Depth First Search Bit Stream SPIHT System,” IEEE International Symposium on Circuits and Systems, Vol. 4, 2001, Page(s): 518-521.
[23]L. M. Ang, H. N. Cheung, and K. Eshraghian, ”A Dataflow-Oriented VLSI Architecture for a Modified SPIHT Algorithm Using Depth-First Search Bit Stream Processing,” 2000. IEEE International Symposium on Circuits and Systems, Vol. 1, 2000, Page(s): 291-294.
[24]R. R. Shively, E. Ammicht, and P. D. Davis, ”Generalizing SPIHT : A Family of Efficient Image Compression Algorithm,” Proceedings. IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 4, 2000, Page(s): 2059-2062.
[25]J. Singh, A. Antoniou, and D. J. Shpak, ”Hardware Implementation of a Wavelet Based Image Compression Coder,” IEEE Symposium on Advances in Digital Filtering and Signal Processing, 1998, Page(s): 169-173.
[26]S. H. Joo, H. Kikuchi, S. Sasaki, and J. Shin, ”A Flexible Zerotree Coding with Low Entropy,” IEEE International Conference on Acoustics, Speech and Signal Processing, Vol. 5, 1998, Page(s): 2685-2688.
[27]A. Said and W. A. Pearlman, “A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” IEEE Transactions on Circuits and Systems for Video Technology, Vol. 63, June 1996, Page(s): 243-250.
[28]G. Voyatzis and I. Pitas, ”Protecting Digital Image Copyrights a Framework,” IEEE Computer Graphics and Applications, Vol. 191, Jan.-Feb. 1999, Page(s): 18-24.
[29]R. B. Wolfgang, C. I. Podilchuk and E. J. Delp, ”Perceptual Watermarks for Digital Images and Video,” Proceedings of the IEEE Vol. 877, July 1999, Page(s): 1108-1126.
[30]D. F. Shen and Y. W. Li, ”Some Insights on Wavelet Based Image Coding,” Proceedings of SPIE on Input/Output and Imaging Technologies, July, 2000.
[31]S. Lin and E. Salari, ”Image Coding Using Wavelet Transform and Classified Vector Quantization,” IEE Proceedings on Vision, Image and Signal Processing, Vol. 1435, Oct. 1996, Page(s): 285-291.
[32]E. H. Adelson and E. Simoncelli, ”Orthogonal Pyramid Transforms for Image Coding,” Proc. SPIE, Vol. 845, Cambridge, MA, Oct. 1987, Page(s): 50-58.
[33]陳同孝, 張真誠, 黃國峰, “數位影像處理技術,”松崗, 2001.
[34]戴裕欽, “具有數位浮水印功能之嵌入式影像編解碼器VLSI設計與實作,” 國立中山大學資訊工程研究所, 碩士論文, 2000.
[35]劉晉吉, “漸進式小波影像編碼系統之參數化設計與晶片設計實現, ”國立成功大學電機工程研究所, 碩士論文, 2000.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔